Mining time series data : case of predicting consumption patterns in steel industry

Fazel, A; Saraee, MH; Shamsinejad, P

Abstract

Analyzing and predicting with Time series is a method which used in different fields, including consumption pattern analyzing and predicting. In this paper, required amount of inventory items have been predicted with time series. At first, desired data mining process is designed and implemented using Clementine data mining tool. We evaluate this process using the dataset from Iran's ZoabAhan steel company. Results show that by using this process not only we can model consumption patterns for the present time but also we can predict required stock items for future with adequate accuracy.

Citation

Fazel, A., Saraee, M., & Shamsinejad, P. (2010, June). Mining time series data : case of predicting consumption patterns in steel industry. Presented at The 2nd International Conference on Software Engineering and Data Mining, Chengdu, China

• Presentation Conference Type: Other
• Conference Name: The 2nd International Conference on Software Engineering and Data Mining
• Conference Location: Chengdu, China
• Start Date: Jun 23, 2010
• End Date: Jun 25, 2010
• Publication Date: Jun 23, 2010
• Deposit Date: Jul 14, 2017
• Publisher URL: http://ieeexplore.ieee.org/document/5542869/
• Related Public URLs: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5510904
• Additional Information: Event Type : Conference